Binary Tree Summation Monte Carlo Method for Potts Models
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چکیده
Efforts to develop better and more efficient algorithms for Monte Carlo simulations have a long history, in which the Fortuin-Kasteleyn (FK) transformation [1] for Potts models has played a pivotal role. The most common use of this transformation has been to create algorithms in which clusters of spins in the Potts model are flipped simultaneously [2, 3]. In this paper, we present a new algorithm using the FK representation in the spirit of recent work by Newman and Ziff [4] on the percolation problem. The method produces independent samples and sums up a large number of configurations for each sweep. The partition function and thermodynamic averages for all values of the temperature T can be computed from a single run. Consider the Potts model with the Hamiltonian,
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تاریخ انتشار 2002